Fetching the paper…
Reading the bibliography…
We present techniques for speeding up the test-time evaluation of large convolutional networks, designed for object recognition tasks.
Object recognition from local scale-invariant features
Lowe, D.G.: · 1999
Earlier work this paper cites.
Rank-one approximation to high order tensors
Zhang, T., Golub, G.H.: · 2001
Earlier work this paper cites.
ImageNet: A Large-Scale Hierarchical Image Database
Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: · 2009
Earlier work this paper cites.
Eigen v3
Guennebaud, G., Jacob, B., et al.: · 2010
Earlier work this paper cites.
Tiled convolutional neural networks
Le, Q.V., Ngiam, J., Chen, Z., Chia, D., Koh, P.W., Ng, A.Y.: · 2010
Earlier work this paper cites.
Improving the speed of neural networks on cpus
Vanhoucke, V., Senior, A., Mao, M.Z.: · 2011
Cited alongside, same era.
Building high-level features using large scale unsupervised learning
Le, Q.V., Ranzato, M., Monga, R., Devin, M., Chen, K., Corrado, G.S., Dean, J., Ng, A.Y.: · 2011
Cited alongside, same era.
Improving neural networks by preventing co-adaptation of feature detectors
Hinton, G.E., Srivastava, N., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.R.: · 2012
Cited alongside, same era.
Imagenet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., Hinton, G.: · 2012
Cited alongside, same era.
Overfeat: Integrated recognition, localization and detection using convolutional networks
Sermanet, P., Eigen, D., Zhang, X., Mathieu, M., Fergus, R., LeCun, Y.: · 2013
Cited alongside, same era.
Predicting parameters in deep learning
Denil, M., Shakibi, B., Dinh, L., Ranzato, M., de Freitas, N.: · 2013
Later among the works it cites.
Fast training of convolutional networks through ffts
Mathieu, M., Henaff, M., LeCun, Y.: · 2013
Later among the works it cites.
Visualizing and understanding convolutional neural networks
Zeiler, M.D., Fergus, R.: · 2013
Later among the works it cites.
Speeding up convolutional neural networks with low rank expansions
Jaderberg, M., Vedaldi, Andrea, Zisserman, A.: · 2014
Closest in time.
Adaptive deconvolutional networks for mid and high level feature learning
Zeiler, M.D., Taylor, G.W., Fergus, R.: · 2025
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Closest in time.